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Solutions
Description
Compatibility Level
Clients
Use cases
EHR integrations
Client types
Differentiators
Keywords
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Company details
Jump to:
Categories
Solutions
Description
Compatibility Level
Clients
Use cases
EHR integrations
Client types
Differentiators
Keywords
Media
Company details
API
API

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Categories

Solutions

Description

Product Description:
Our API enables real-time transformation of unstructured healthcare data into structured data that can be used for search and analysis. Identify and extract over 9 million healthcare concepts with a single line of code.
About ScienceIO:
More than 80% of healthcare data is unstructured; it is either physical or in a digital format that requires manual labor to analyze, such as images or typed/handwritten notes. Healthcare runs on notes, scans, and PDFs. Because healthcare data is designed for manual labor, it cannot be easily searched, analyzed, or used to improve patients' quality of care or reduce cost of care. Manual labor does not scale, and the data is growing: 2 zettabytes of healthcare data are generated each year. Historically, the healthcare industry has invested in protocols for the structured data it has, digitizing analog data but leaving it unstructured, and brute-forcing the unstructured data problem through manual labor. These solutions have plateaued. We have to solve the unstructured data problem in healthcare. ScienceIO envisions a future where we enable all healthcare companies — across R&D, clinical trials, real world evidence, digital health, reimbursement, to care delivery — to learn from their data in real-time, so we can develop the next generation of healthcare solutions.
Product Description:

AI to review all patient data, ensure diagnoses are not missed, and automating note-writing.

Regard uses proprietary algorithms to automatically diagnose and document conditions on behalf of inpatient providers. These automatically-generated notes save providers time, reduce coding queries, and have a dramatic impact to hospital finances.

About Regard:

Regard is an AI-powered clinical co-pilot that automatically diagnoses patients and writes notes for physicians. On average clinicians save 2-3 hours per day and each provider generates an additional $100,000 in revenue every year. Hospitals see a $3-6M revenue improvement from just their first department on Regard. Best of all, physicians love the software and it improves patient care.

Compatibility level

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Clients

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Use Cases

Description:

None provided

Pediatric use cases:

None provided

Users:

None provided

Description:

Automatically review charts and diagnose patients to save time, reduce burnout, improve care, and improve key hospital metrics.

Pediatric use cases:

None provided

Users:

Diagnosing providers: hospitalists, MDs/DOs, Advanced Practice Providers

EHR Integrations

Integrations:

None provided

EMR Integration & Relevant Hardware:

None provided

EMRs Supported:

None provided

Hardware Compatibility:

None provided

Integrations:

Acute care EMR, Ambulatory EMR

EMR Integration & Relevant Hardware:

Recommended, but not required

EMRs Supported:

Epic, Cerner

Hardware Compatibility:

Desktop

Client Types

None provided

Differentiators

Differentiators vs EHR Functionality:

None provided

Differentiators vs Competitors:

None provided

Differentiators vs EHR Functionality:

Regard diagnoses automatically. The EHR supports overall health system goals and is the operating system for all functions, but Regard expands your care team using AI. Regard diagnoses, recommends treatments, and automates documentation to ensure patient safety, improve clinician quality of life, and supercharge CDI & rev cycle.

Differentiators vs Competitors:

Regard drafts the note just like an AI resident before the clinician even sees the patient. By doing this upstream, we can reduce the burden on the clinician and supercharge downstream tools like clinical alerts, CAPD, and CDI.

Regard takes a holistic view of the patient to improve safety, reduce medical errors, suggest improvements to care, and ensure that the documentation is complete & accurate.

Keywords

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Downloads

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Alternatives

Company Details

Founded in 2019

Founded in 2017

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